My role primarily revolves around reinforcing students’ understanding and application of key data science concepts, including pandas, scikit-learn, Principal Component Analysis (PCA), logistic regression, multiple linear regression, and clustering. More information can be found at the official course website.

Tutoring and Instructional Support

I regularly conduct tutoring sessions that focus on practical and theoretical aspects of data manipulation and analysis using pandas, a critical library in Python for data science. These sessions are tailored to help students grasp complex data structures and operations essential for real-world data analysis.

Grading and Assessment

My responsibilities include grading assignments and projects where students apply various machine learning algorithms. This involves assessing their proficiency in scikit-learn for implementing models like logistic regression and multiple linear regression, ensuring they understand these models’ intricacies and applications.

Office Hours and Personalized Guidance

I hold office hours to provide additional support, particularly in advanced topics like PCA and clustering algorithms. During these sessions, I focus on clarifying students’ doubts, offering insights into the practical implementation of these techniques, and guiding them through the nuances of model selection and data interpretation.